About: 6GCVAE: Gated Convolutional Variational Autoencoder for IPv6 Target Generation

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	6GCVAE: Gated Convolutional Variational Autoencoder for IPv6 Target Generation
Creator	Cui, Tianyu Gou, Gaopeng Xiong, Gang
Source	PMC
abstract	IPv6 scanning has always been a challenge for researchers in the field of network measurement. Due to the considerable IPv6 address space, while recent network speed and computational power have been improved, using a brute-force approach to probe the entire network space of IPv6 is almost impossible. Systems are required an algorithmic approach to generate more possible active target candidate sets to probe. In this paper, we first try to use deep learning to design such IPv6 target generation algorithms. The model effectively learns the address structure by stacking the gated convolutional layer to construct Variational Autoencoder (VAE). We also introduce two address classification methods to improve the model effect of the target generation. Experiments indicate that our approach 6GCVAE outperformed the conventional VAE models and the state of the art target generation algorithm in two active address datasets.
has issue date	2020-04-17(xsd:dateTime)
bibo:doi	10.1007/978-3-030-47426-3_47
has license	no-cc
sha1sum (hex)	25c128e9ab8e12f9fbbac669c961cd64d8a5940d
schema:url	https://doi.org/10.1007/978-3-030-47426-3_47
resource representing a document's title	6GCVAE: Gated Convolutional Variational Autoencoder for IPv6 Target Generation
has PubMed Central identifier	PMC7206168
schema:publication	Advances in Knowledge Discovery and Data Mining
resource representing a document's body	covid:25c128e9ab8e12f9fbbac669c961cd64d8a5940d#body_text
is schema:about of	named entity 'algorithm' named entity 'brute-force' named entity 'Generation' named entity 'DEEP LEARNING' named entity 'CONSIDERABLE' named entity 'models' named entity 'conventional' named entity 'learns' named entity 'IPv6' named entity 'field' named entity 'generate' named entity 'model' named entity 'address space' named entity 'active' named entity 'algorithms' named entity 'generation' named entity 'IPv6' named entity 'convolutional layer' named entity 'deep learning' named entity 'convolutional layer' named entity 'convolutional layer' named entity 'entropy' named entity 'cross-entropy' named entity 'recursive algorithm' named entity 'batch processing' named entity 'number of clusters' named entity 'IPv6' named entity 'deep learning' named entity 'ICMPv6' named entity 'convolutional network' named entity 'Entropy' named entity 'network address' named entity 'IPv6' named entity 'nybble' named entity 'IPv6 address' named entity 'IPs' named entity 'EUI-64' named entity 'IID' named entity 'Entropy' named entity 'vector' named entity 'MAC address' named entity 'text generation' named entity 'pseudo-random' named entity 'IPv6' named entity 'sampling' named entity 'entropy' named entity 'state of the art' named entity 'hidden layers' named entity 'IPv6' named entity 'IPv6 address' named entity 'IPv6' named entity 'parallel computing' named entity 'IPv6' named entity '16 bits' named entity 'sampling' named entity 'SLAAC' named entity 'algorithm' named entity 'IPv6' named entity 'prior distribution' named entity 'convolutional network' named entity 'WMT' named entity 'Convolution Layer' named entity 'convolutional layer' named entity 'statistical model' named entity 'IID' named entity 'Bayesian network' named entity 'Variational Autoencoder' named entity 'softmax' named entity 'sampling' named entity 'IPv6' named entity 'IPv6 address' named entity 'correlation' named entity 'IPv6' named entity 'Natural Language Processing' named entity 'fingerprint' named entity 'neural networks' named entity 'hexadecimal' named entity 'WMT' named entity 'Deep neural network' named entity 'hexadecimal' named entity 'vector'

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